Mobile communications, such as mobile telephony, is a technology that is continuously gaining an increased user base. Similarly, as new technologies emerge, they will co-exist with older standards. Furthermore, different geographical areas have different communication standards and spectrum planning. As a User Equipment (UE), such as a mobile telephone is switched on it searches for available network carriers according to a stored history list of Radio Access Technologies (RAT) and carriers. Through this list information is available on which RATs are available and at what carrier frequencies, and this makes it easy for a UE to quickly connect to a preferred carrier of a preferred RAT. However, looking at all possible cellular environments a UE might experience at different places of the world, it is obvious that it is of importance to quickly find a suitable network to camp on once the UE is switched on at a new geographical position where the stored history list of RATs and carriers are not valid.
The classical RAT detection and cell search approach uses Received (RX) energy detection over a grid of test locations in frequency, followed by synchronization attempts with different RAT formats. For each candidate location, the Radio Frequency (RF) stage is tuned to the corresponding frequency and the received energy is evaluated. However, the traditional approach is becoming increasingly inefficient as the hypothesis grid becomes denser, the number of bands increases, and the set of possible RATs grows.
The American patent application US2007217550 discloses a system having a signal processor for detection of a signal type of a signal. One embodiment is designed to determine a first variable which is characteristic of a first spectrum element of the signal spectrum, and to determine a second variable which is characteristic of a second spectrum element of the signal spectrum, a system for determination of a ratio between the first variable and the second variable, and a detector which is designed to detect the signal type on the basis of the ratio.
The American patent application US2011045781 discloses techniques for sensing wireless communications in television frequency bands, which may be implemented by a sensing device comprising a sensing unit, a power spectral density (PSD) estimation unit, a filter unit, a candidate selection unit, an analysis unit and a decision unit. The sensing unit senses a signal in the television frequencies bands. The PSD estimation unit calculates an estimate of a PSD for the sensed signal. The filter unit filters the estimated PSD. The candidate selection unit analyzes the filtered PSD to identify a candidate frequency representative of a potentially in use frequency. The analysis unit computes a test statistic for the candidate frequency. The decision unit compares the test statistic to a threshold to identify whether the candidate frequencies is actively in use by wireless communication devices.
The techniques disclosed in these two patent applications are aimed at finding or estimating bandwidths of signals and are not suited for signals which are of a flat character and subsequently not suited for detecting RATs such as WCDMA and LTE. They are also not suited for use in a packed frequency environment where different signals may be so closely arranged (or even overlap) that their bandwidths are not distinguishable from one another.
To make the process of finding a RAT to connect to faster, The European patent application EP08853764.2, which is incorporated herein by reference, has introduced a Fast Fourier Transformation (FFT) scan over a frequency band, in order to get a power spectral density estimate, and then via matched filters in frequency domain be able to detect cellular systems employing different bandwidths. Frequency domain scanning speeds up the cell search process significantly, as the probable carrier frequency is established quite exactly prior to performing a synchronization attempt. Furthermore, in terminals with Long Term evolution (LTE) functionality (LTE being one example of a RAT), this approach leads to negligible incremental complexity, since the existing FFT hardware may be used for the scanning operation.
With the FFT scan as described above, it is possible to localize transmission bands, and distinguish between bands of different bandwidths. However, only looking at the matched filter outputs, there are problems discriminating between some RAT configurations. For instance, a Wideband Code Division Multiple Access (WCDMA) carrier and a 5 MHz LTE carrier occupy a frequency region of approximately the same width. Similarly, several adjacent WCDMA carriers could be confused with a 10 or 20 MHz LTE carrier. In the first stage of LTE deployments, mixed WCDMA and LTE carrier allocations are expected to be commonplace, as well as mixes of GSM and WCDMA deployment which already exist, and this gives and will give rise to frequent ambiguity. Extending this to include GSM too even more mix-up can occur. For example as in detecting GSM spectral density as part of a WCDMA cell. Thus, in order to determine the correct RAT according to the prior art method, synchronization attempts according to all relevant possible carrier configurations (RAT, Bandwidth (BW), etc.) should be carried out, once a presumed carrier or a carrier set is identified. This leads to notable extra time expenditure in the initial connection establishment and cell search process.
Thus, it is of interest to develop methods and apparatus to quickly be able to distinguish between different RATs or RAT combinations that may occupy the same bandwidth, without having to resort to explicit RAT-specific synchronization procedures. One problem to be solved is thus to cope with first time synchronization, or when the signal environment has changed significantly, e.g. switching on the communication apparatus in a new geographical situation. This problem has been solved by EP08853764.2. This solution is, however, somewhat limited. There is thus a need for an alternative solution to this problem.
Another approach is to receive signals present in a frequency range; transforming received signals into frequency domain; estimating power spectral density from transformed signals; estimating probability of different communication modes by correlating the estimated power spectral density with power spectral density signatures of said different communication modes; and performing cell search according to estimated most probable communication mode.
Still, when different operation modes have power spectral density signatures that resembles each other, it may be hard to determine which the correct communication mode is since more than one seems to be probable.
There is thus a need for an apparatus that is able to quickly ascertain what available RATs exist and to be able to discern between different RATs even in an environment where different carriers operate on carrier frequencies that are closely arranged in a frequency range and that is suitable for channels having a frequency spectrum being of a flat character.